Investigating the Effectiveness of Using Structured and Unstructured Google Classroom on Grammar Learning Among Omani EFL Post-Basic Learners, and Perceived Benefits and Challenges
Bibliographic record
Abstract
This study investigated the effectiveness of Google Classroom as a tool to improve grammar acquisition of Omani EFL learners. It analyzed students’ responses to structured and unstructured Google Classroom frameworks, to examine how each framework impacts performance. Perceptions concerning the use of Google Classroom, and the challenges encountered when using the platform were also identified. The sample of the study included two groups (structured (61) and unstructured (54), n= 115) from grade 11 students from one of the schools in Muscat Governorate in the academic year 2020-2021. Two instruments were used to collect data: a grammar achievement test (pre- post-test) and a questionnaire. The results of the study revealed a statistically significant improvement in students’ grammar performance, in favor of the structured Google Classroom group. All students were highly positive about using Google Classroom, finding it useful, enjoyable and easy. In the light of these findings, implications and recommendations are provided.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".